mne.beamformer.Beamformer#
- class mne.beamformer.Beamformer[source]#
A computed beamformer.
Notes
New in version 0.17.
Methods
__contains__
(key, /)True if the dictionary has the specified key, else False.
x.__getitem__(y) <==> x[y]
__iter__
(/)Implement iter(self).
__len__
(/)Return len(self).
clear
()copy
()Copy the beamformer.
fromkeys
(iterable[, value])Create a new dictionary with keys from iterable and values set to value.
get
(key[, default])Return the value for key if key is in the dictionary, else default.
items
()keys
()pop
(k[,d])If key is not found, d is returned if given, otherwise KeyError is raised
popitem
(/)Remove and return a (key, value) pair as a 2-tuple.
save
(fname[, overwrite, verbose])Save the beamformer filter.
setdefault
(key[, default])Insert key with a value of default if key is not in the dictionary.
update
([E, ]**F)If E is present and has a .keys() method, then does: for k in E: D[k] = E[k] If E is present and lacks a .keys() method, then does: for k, v in E: D[k] = v In either case, this is followed by: for k in F: D[k] = F[k]
values
()- __contains__(key, /)#
True if the dictionary has the specified key, else False.
- __getitem__()#
x.__getitem__(y) <==> x[y]
- __iter__(/)#
Implement iter(self).
- __len__(/)#
Return len(self).
- clear() None. Remove all items from D. #
- copy()[source]#
Copy the beamformer.
- Returns
- beamformerinstance of
Beamformer
A deep copy of the beamformer.
- beamformerinstance of
- fromkeys(iterable, value=None, /)#
Create a new dictionary with keys from iterable and values set to value.
- get(key, default=None, /)#
Return the value for key if key is in the dictionary, else default.
- items() a set-like object providing a view on D's items #
- keys() a set-like object providing a view on D's keys #
- pop(k[, d]) v, remove specified key and return the corresponding value. #
If key is not found, d is returned if given, otherwise KeyError is raised
- popitem(/)#
Remove and return a (key, value) pair as a 2-tuple.
Pairs are returned in LIFO (last-in, first-out) order. Raises KeyError if the dict is empty.
- save(fname, overwrite=False, verbose=None)[source]#
Save the beamformer filter.
- Parameters
- fname
str
The filename to use to write the HDF5 data. Should end in
'-lcmv.h5'
or'-dics.h5'
.- overwritebool
If True (default False), overwrite the destination file if it exists.
- verbosebool |
str
|int
|None
Control verbosity of the logging output. If
None
, use the default verbosity level. See the logging documentation andmne.verbose()
for details. Should only be passed as a keyword argument.
- fname
- setdefault(key, default=None, /)#
Insert key with a value of default if key is not in the dictionary.
Return the value for key if key is in the dictionary, else default.
- update([E, ]**F) None. Update D from dict/iterable E and F. #
If E is present and has a .keys() method, then does: for k in E: D[k] = E[k] If E is present and lacks a .keys() method, then does: for k, v in E: D[k] = v In either case, this is followed by: for k in F: D[k] = F[k]
- values() an object providing a view on D's values #
Examples using mne.beamformer.Beamformer
#
Compute source power using DICS beamformer
Compute cross-talk functions for LCMV beamformers